Blood dna methylation biomarker diagnostic test for anxiety and depressive disorders

ABSTRACT

A method for diagnosing or giving a prognosis for anxious temperament or trait-like anxiety in a human or non-human primate subject comprising the steps of (a) obtaining DNA from a blood or saliva sample from the subject and (b) quantifying methylation in a set of differentially methylated regions (DMRs) selected from SEQ ID NOs: 1-32, 34-44, 46-53, and 55-74, GCTCA, CGCACCG, AGAGGCAG, and AGCTCG or DMR-associated genes selected from DIP2C, GRB10, INPP5A, C17ORF97, PDXK, CACNA2D4, TRAPPC9, CRTC1, MEGF6, HIVEP3, OPCML, PITPNM2, ZFPM1, RAP1GAP2, NFATC1, RNF126, FSTL3, GNAS, SH3BP2, NEURL1B, MAD1L1, HSPA12B, IGF2, PEG10, PEG3, SLC16A3, SYTL1, and ZIM2, wherein a significant change methylation indicates the present of anxious temperament or trait-like anxiety, wherein the change is relative to DNA from a second human or non-human primate who does not have anxious temperament or trait-like anxiety. Also disclosed is a biomarker panel of DMR and DMR-associated genes for the diagnosis or prognosis of anxious temperament or trait-like anxiety.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No. 16/898,897, filed Jun. 11, 2020, which claims priority to U.S. Provisional Application No. 62/860,022, filed Jun. 11, 2019, both of which are incorporated herein by reference in their entireties.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

Not applicable

REFERENCE TO THE SEQUENCE LISTING

The instant application contains a Sequence Listing which has been submitted electronically in XML format and is hereby incorporated by reference in its entirety. The XML copy, created on Nov. 22, 2022, is named USPTO--221122--APP--P190178U503--SEQ_LIST.xml and is 72,048 bytes in size.

BACKGROUND

Anxiety is frequently characterized by a negative affective response that is associated with the anticipation of encountering a potential threat. Trait-like anxiety in humans and non-human primates is associated with stable individual differences in hypothalamic—pituitary—adrenal (HPA) axis activation and amygdala function. HPA activation results in the release of cortisol, and increased cortisol concentrations in children and adolescents can be linked to inhibited behaviors and anxiety that often persist throughout life.

Additionally, a loss of the ‘natural’ circadian decline in afternoon/evening cortisol levels has been correlated with shyness and later alterations in behavior, including internalizing problems, suggesting that late-in-the day cortisol levels in children and adolescents may be an index of early life and current stress exposure as well as altered behaviors. High afternoon cortisol levels in childhood are also negatively correlated with amygdala-prefrontal cortex connectivity in adolescents and adults, indicating that a disruption in amygdala function is related to trait-like anxiety. In fact, anxiety prone individuals show greater amygdala activation during emotion processing tasks, further supporting a central role of the amygdala in processing of fearful stimuli.

Moreover, lesions in the central nucleus of the amygdala of non-human primates results in decreased adrenocorticortropic hormone (ACTH) concentrations before and after stressful conditions. Finally, higher and prolonged amygdala metabolism following a stressful challenge results in increased anxiety-like behaviors (e.g., freezing) in young rhesus monkeys, suggesting that the timing of amygdala activation and deactivation, in both humans and rhesus monkeys, is associated with trait-like anxiety.

Genetic data suggest that common anxiety disorders like generalized and social anxiety disorders are ˜20%-40% heritable and that environmental factors—potentially including epigenetic modifications—likely account for much of the remaining variability. Studies using adult post-mortem brain tissue support a role for DNA methylation (i.e., 5-methylcytosine [5mC]) in the development of anxiety, bipolar disorder, schizophrenia, and major depressive disorder.

SUMMARY OF THE INVENTION

In a first aspect, provided herein is a method of amplifying at least one of six differentially methylated region (DMR) associated genes comprising the steps of: (a) providing a reaction mixture comprising bisulfite modified target DNA from a subject and at least one pair of primers designed to amplify at least one DMR-associated gene selected from the group consisting of DIP2C, INPP5A, PDXK, GNAS, GRB10, and TRAPPC9 wherein the primer pair comprises a first and a second primer that are complementary to the DMR-associated gene; (b) heating the reaction mixture to a first predetermined temperature for a first predetermined time; (c) cooling the reaction mixture to a second predetermined temperature for a second predetermined time under conditions to allow the first and second primers to hybridize with their complementary sequences on the target DNA; and (d) repeating steps (b) and (c) wherein an amplified target DNA sample is formed. In some embodiments, the reaction mixture additionally comprises a polymerase and a plurality of free nucleotides comprising adenine, thymine, cytosine, and guanine. In some embodiments, the reaction mixture additionally comprises a reaction buffer and MgCl₂.

In some embodiments, in step (a), (i) a first reaction mixture comprising a first portion of bisulfite modified target DNA and a pair of primers designed to amplify DIP2C; (ii) a second reaction mixture comprising a second portion of bisulfite modified target DNA and a pair of primers designed to amplify INPP5A; (iii) a third reaction mixture comprising a third portion of bisulfite modified target DNA and a pair of primers designed to amplify PDXK; (iv) a forth reaction mixture comprising a forth portion of bisulfite modified target DNA and a pair of primers designed to amplify GNAS; (v) a fifth reaction mixture comprising a fifth portion of bisulfite modified target DNA and pair of primers designed to amplify GRB10; and (vi) a sixth reaction mixture comprising a sixth portion of bisulfite modified target DNA and a pair of primers designed to amplify TRAPPC9 are provided.

In some embodiments, the primers are specific for a DMR selected from the group consisting of SEQ ID NOs: 7-18, 50-53, 55-59, 67-69, 73, and 74, AGAGGCAG, and AGCTCG. In some embodiments, at one of primers in the primer pair is biotinylated.

In some embodiments, the methods described herein include providing subsequent reaction mixtures comprising subsequent portions of bisulfite modified target DNA and a pair of primers designed to amplify one or more DMR-associated genes selected from the group consisting of C17ORF97, CACNA2D4, CRTC1, MEGF6, HIVEP3, OPCML, PITPNM2, ZFPM1, RAP1GAP2, NFATC1, RNF126, FSTL3, SH3BP2, NEURL1B, MAD1L1, HSPA12B, IGF2, PEG10, PEG3, SLC16A3, SYTL1, and ZIM2. In some embodiments, the primers are designed to amplify a DMR selected from the group consisting of SEQ ID NOS: 1-6, 19-32, 34-44, 46-49, 60-66, and 70-72, GCTCA, and CGCACCG.

In some embodiments, the target DNA is isolated from a blood sample or a saliva sample form the subject. In some embodiments, the subject is a human or non-human primate.

In a second aspect, provided herein is a biomarker panel comprising probes specific to DIP2C, INPP5A, PDXK, GNAS, GRB10, and TRAPPC9. In some embodiments, the biomarker panel additionally comprises pairs of primers designed to amplify DIP2C, INPP5A, PDXK, GNAS, GRB10, and TRAPPC9.

In some embodiments, either the probes or the primers are arrayed on a substrate. In some embodiments, the substrate is selected from the group consisting of a chip, a bead, a plate, a microfluidic device, or a multiwall plate.

In some embodiments, the primers are designed to amplify SEQ ID NOs: 7-18, 50-53, 55-59, 67-69, 73, and 74, AGAGGCAG, and AGCTCG.

In some embodiments, the biomarker panel additionally comprises probes specific to HIVEP3, C17orf97, ZFPM1, RAP1GAP2, NFATC1, IGF2, SLC16A3, and SYTL1. In some embodiments, the probes are specific to SEQ ID NOs: 3-6, 19-20, 27-32, and 34-37 and GCTCA.

In some embodiments, the biomarker panel additionally comprises probes specific to CACNA2D4, CRTC1, MEGF6, OPCML, PITPNM2, ZIM2, RNF126, FSTL3, SH3BP2, NEURL1B, MAD1L1, HSPA12B, PEG10, and PEG3. In some embodiments, the probes are specific to SEQ ID NOs: 1-2, 21-26, 38-44, 46-49, 60-66, and 70-72 and CGCACCG.

In a third aspect, provided herein is a biomarker panel comprising the sequences of SEQ ID NOs: 7-18, 50-53, 55-59, 67-69, 73, and 74, AGAGGCAG, and AGCTCG. In some embodiments, the sequences of SEQ ID NOs: 7-18, 50-53, 55-59, 67-69, 73, and 74, AGAGGCAG, and AGCTCG are arrayed on a substrate. In some embodiments, the substrate is selected from the group consisting of a chip, a bead, a plate, a microfluidic device, or a multiwall plate. In some embodiments, the biomarker panel additionally comprises the sequences of SEQ ID NOs: 1-2, 21-26, 38-44, 46-49, 60-66, and 70-72 and CGCACCG. In some embodiments, the biomarker panel additionally comprise the sequences of SEQ ID NOs:3-6, 19-20, 27-32, and 34-37 and GCTCA.

In a forth aspect, provided herein is a method of diagnosing anxious temperament in a subject comprising the steps of: (a) obtaining a blood sample or saliva sample from the subject; (b) isolating target DNA from the sample obtained in (a); (c) contacting a biomarker panel as described herein with the isolated target DNA; (d) amplifying DMR-associated genes DIP2C, INPP5A, PDXK, GNAS, GRB10, and TRAPPC9; (e) quantifying methylation in the amplified DMR-associated genes, whereby a change in methylation of at least 10% compared to methylation in the same genes from a subject unaffected by anxious temperament indicates the presence of anxious temperament in the subject.

BRIEF DESCRIPTION OF DRAWINGS

The patent or patent application file contains at least one drawing in color. Copies of this patent or patent application publication with color drawings will be provided by the Office upon request and payment of the necessary fee.

FIG. 1 shows overlap of differentially methylated region associated genes identified from monkey brain, monkey blood, and human blood.

FIG. 2 shows differentially methylated region associated genes including multiple CpGs with greater than 10% differential methylation (shown as black tick marks at bottom). DNA methylation profiles for the anxious (red) and unaffected (control; blue) twin-pairs are shown and the genomic region of significance between twin-pairs is highlighted (peach). Each corresponding co-twin is indicated by a different line pattern (pair A=solid; B=dashed; C=dash+dot).

DETAILED DESCRIPTION OF THE DISCLOSURE

Recent study in young monkeys, as well as studies in humans, identified differentially methylated genes that are implicated as risk factors for anxiety and depressive disorders. Thus, these studies support the hypothesis that DNA methylation may have an important role in the risk to develop trait-like anxiety. However, these studies have relied heavily on the ability to access brain tissue. Focusing studies on anxiety-related DNA methylation profiles in blood has the potential to provide tools that could be clinically utilized to improve diagnostic and treatment strategies. Therefore, a need in the art exists for blood sample or saliva sample-based diagnostic tests for anxiety in primates.

The present disclosure describes blood sample or saliva sample based assays for the diagnosis, prognosis, and modified therapeutic response to anxiety in primates. The present disclosure describes differentially methylated regions (DMRs) associated with 22 different genes that are characteristic of anxious temperament and trait-like anxiety in primates. These characteristic biomarkers may be used to assay methylation in DNA isolated from a primate blood sample or a primate saliva sample. These characteristic biomarkers may be used in the development of a screening panel, a resequencing panel, or a diagnostic kit for the processing of DNA isolated from a primate blood sample or a primate saliva sample.

As used herein, “anxious temperament,” or “AT” refers to the disposition of a human or non-human primate who is sensitive to new social experiences, shows increased freezing behavior, decreased communications, and increased pituitary-adrenal and autonomic activity. In non-human primates, AT can be computed and quantified as a composite measure among vocalizations, cortisol levels and freezing time assessed during the no eye contact condition of the human intruder paradigm. An individual can have an AT composite phenotype score between −1.48 to 1.43, with the higher scores correlated with increased freezing, decreased communication, increased cortisol levels, or a combination thereon. At risk children score at least 1.5 standard deviations above and below the mean on at least one of eight parent-reported symptom scales of the Health and Behavior Questionnaire (Essex M J, et al., Biological psychiatry, 2002). Because AT reflects a continuous trait-like variable, individuals will have a broad range of AT-related scores.

As used herein, “trait-like anxiety,” refers to stable individual differences in hypothalamic-pituitary-adrenal (HPA) axis activation and amygdala function. (Kagan J, et al., Biological psychiatry. 1999; Kalin N H, Shelton S E. Ann N Y Acad Sci. 2003).

Biomarker Candidates

Described herein are differentially methylated regions associated with 22 different genes that are characteristic of anxious temperament and trait like anxiety.

As used herein, “differentially methylated region” or “DMR” refers to CpG dinucleotide regions with a significant increase (hypermethylation) or a significant decrease (hypomethylation) in methylation (e.g, 5-methylcytosine (5mC)) relative to control. The control is considered the level of methylation measured in a DNA sample from a primate unaffected by AT or trait-like anxiety. In some embodiments, the DMR corresponds to a region with a change in methylation of at least about 8%, at least about 10%, at least about 12%, at least about 15% or at least about 20% when compared to control. In some embodiments, the DMR corresponds to a region with at least 10% increase in methylation compared to control. In some embodiments, the DMR corresponds to a region with at least 10% decrease in methylation compared to control.

As used herein, “significant increase” refers to an increase with a statistical significance of p<0.05 when compared to control.

As used herein, “significant decrease” refers to a decrease with a statistical significance of p<0.05 when compared to control.

As used herein, “differentially methylated region-associated genes” or “DMR-associated genes” refers to the genes in which the DMRs are located or most closely associated with. In some embodiments, the DMR may be in the coding region of the DMR-associated gene. In some embodiments, the DMR may be in the promoter region of the DMR-associated gene.

DMR biomarker candidates associated with genes DIP2C, GRB10, INPP5A, C17ORF97, PDXK, CACNA2D4, TRAPPC9, CRTC1, MEGF6, HIVEP3, OPCML, PITPNM2, ZFPM1, RAP1GAP2, NFATC1, RNF126, FSTL3, GNAS, SH3BP2, NEURL1B, MAD1L1, HSPA12B, IGF2, PEG10, PEG3, SLC16A3, SYTL1, and ZIM2 show significant (p<0.05) changes in methylation in target regions when DNA samples from anxious and unaffected (control) primates are compared.

Applicant notes that U.S. Provisional Application No. 62/860,022, the whole genome bisulfite sequence data was mapped to the rhesus macaque genome (rheMac8) and then annotated to “refseq” genes to get the gene symbols to orient the location of DNA methylation data to genes. This approach resulted in about ˜6,000 gene symbol annotations to the data. However, this annotation was limited due to the low number of gene symbols found related to the data. Subsequence improved gene annotation methods and the use of Ensembl gene symbols provided more than 16,000 gene annotations to the rhesus macaque data. RNA sequencing data from the rhesus macaque brain tissue and the RSEM pipeline was also annotated to the Ensembl gene symbols. Using Ensembl gene symbols for both the DNA methylation and RNA sequence data allowed comprehensive comparisons between these data. Therefore, while particular gene symbols may be revised or updated from U.S. Provisional Application No. 62/860,022, this is an artifact of the gene annotation assembly used. The updated gene symbols are reflected herein and consistent with the DMRs recited in the provisional application.

TABLE 1 Anxiety-Associated Genes Gene Symbol Gene Name DIP2C disco interacting protein 2 homolog C GRB10 growth factor receptor bound protein 10 INPP5A inositol polyphosphate-5-phosphatase A C17orf97 chromosome 16 open reading frame, human C17orf97 PDXK pyridoxal kinase CACNA2D4 calcium voltage-gated channel auxiliary subunit alpha2delta 4 TRAPPC9 trafficking protein particle complex 9 CRTC1 CREB regulated transcription coactivator 1 MEGF6 multiple epidermal growth factor-like domains protein 6 HIVEP3 human immunodeficiency virus type I enhancer-binding protein 3 OPCML opioid-binding cell adhesion molecule PITPNM2 phosphatidylinositol transfer protein membrane associated 2 ZFPM1 zinc finger protein multitype 1 RAP1GAP2 Ras-proximate-1 (RAP1) GTPase activating protein 2 NFATC1 nuclear factor of activated T-cells, cytoplasmic 1 RNF126 ring finger protein 126 FSTL3 follistatin Like 3 GNAS guanine nucleotide-binding protein G(s) subunit alpha SH3BP2 SH3 domain-binding protein 2 NEURL1B neuralized E3 ubiquitin protein ligase 1B MAD1L1 mitotic arrest deficient 1 like 1 HSPA12B heat shock protein family A (Hsp70) member 12B IGF2 insulin like growth factor 2 PEG10 paternally expressed 10 PEG3 paternally expressed 10 SLC16A3 solute carrier family 16 member 3 SYTL1 synaptotagmin like 1 ZIM2 zinc Finger Imprinted 2

DMR biomarkers are recited in Table 2. These biomarkers represent CpG regions with at least about 10% differential methylation in target regions when DNA samples from anxious and unaffected (control) primates are compared. Differential methylation includes both hypermethylation and hypomethylation.

TABLE 2 Overlapping AT-related DMRs SEQ ReSeq DMR ID Chromosome Start End Gene Symbol panel ID Overlap Status NO: Chr 1 3503131 3503245 MEGF6 RhBrn_26 ** Hyper 1 Chr 1 3540349 3540490 MEGF6 HuBld_196 ** Hyper 2 Chr 1 27349740 27349796 SYTL1 RhBld_38 ## Hyper 3 Chr 1 27349814 27350119 SYTL1 HuBld_ 4 ## Hyper 4 Chr 1 41540915 41541160 HIVEP3 HuBld_171 ## Hyper 5 Chr 1 41618187 41618276 HIVEP3 RhBld_22 ## Hyper 6 Chr 10 309028 309164 DIP2C RhBld_230 *** Hyper 7 Chr 10 329499 329561 DIP2C RhBld_243 *** Hyper 8 Chr 10 355287 355459 DIP2C RhBld_232 *** Hyper 9 Chr 10 355461 355490 DIP2C RhBld_1000 *** Hyper 10 Chr 10 355492 355503 DIP2C RhBld_1001 *** Hyper 11 Chr 10 355504 355516 DIP2C RhBld_1002 *** Hyper 12 Chr 10 355517 355541 DIP2C RhBld_1003 *** Hyper 13 Chr 10 413853 414117 DIP2C HuBld_28 *** Hyper 14 Chr 10 484804 484931 DIP2C RhBrn_215 *** Hyper 15 Chr 10 132607036 132607056 INPP5A RhBrn_218 *** Hypo 16 Chr 10 132607057 132607061 INPP5A RhBrn_1002 *** Hypo 17 Chr 10 132616356 132616412 INPP5A HuBld_122 *** Hypo 18 Chr 11 2133265 2133335 IGF2; RhBld_355 ## Hyper 19 Chr 11 2133341 2133722 IGF2; INS-IGF2 HuBld_67 ## Hyper 20 Chr 11 133081982 133082177 OPCML HuBld_56 ** Hyper 21 Chr 12 1811666 1811837 CACNA2D4 HuBld_180 ** Hyper 22 Chr 12 1838231 1838295 CACNA2D4 RhBrn_300 ** Hyper 23 Chr 12 1842428 1842506 CACNA2D4 RhBrn_298 ** Hyper 24 Chr 12 123034226 123034317 PITPNM2 HuBld_153 ** Hypo 25 Chr 12 123077953 123078020 PITPNM2 RhBrn_295 ** Hypo 26 Chr 16 88500291 88500408 ZFPM1 HuBld_154 ## Hypo 27 Chr 16 88534642 88534701 ZFPM1 RhBld_495 ## Hypo 28 Chr 17 410141 410147 C17orf97 RhBld_1008 ## Hypo 29 Chr 17 414205 414425 C17orf97 HuBld_143 ## Hypo 30 Chr 17 2837445 2837518 RAP1GAP2 RhBld_403 ## Hypo 31 Chr 17 2852762 2852873 RAP1GAP2 HuBld_159 ## Hypo 32 Chr 17 82235989 82236062 SLC16A3 HuBld_170 ## Hypo Chr 17 82238736 82238899 SLC16A3 RhBld_404 ## Hypo 34 Chr 18 79436203 79436269 NFATC1 RhBld_449 ## Hyper 35 Chr 18 79509085 79509203 NFATC1 HuBld_123 ## Hyper 36 Chr 18 79523293 79523358 NFATC1 RhBld_455 ## Hyper 37 Chr 19 659125 659132 RNF126 RhBrn_491 ** Hyper 38 Chr 19 659138 659172 RNF126 RhBrn_1011 ** Hyper 39 Chr 19 659175 659216 RNF126 RhBrn_1012 ** Hyper 40 Chr 19 659431 659723 RNF126 HuBld_79 ** Hyper 41 Chr 19 676722 676962 FSTL3 HuBld_108 ** Hypo 42 Chr 19 18762214 18762355 CRTC1 RhBrn_478 ** Hyper 43 Chr 19 18777827 18778074 CRTC1 HuBld_49 ** Hyper 44 Chr 19 56838765 56839239 ZIM2; PEG3 HuBld_13 ** Hypo Chr 19 56840640 56840712 RF02151; PEG3 RhBrn_1009 ** Hypo 46 Chr 19 56840714 56840745 RF02151; PEG3 RhBrn_1010 ** Hypo 47 Chr 20 3751818 3752296 HSPA12B HuBld_2 ** Hyper 48 Chr 20 3751944 3752172 HSPA12B RhBrn_246 ** Hyper 49 Chr 20 58839989 58840198 GNAS; GNAS-AS1 HuBld_38 *** Hyper 50 Chr 20 58850827 58850895 GNAS; GNAS-AS1 HuBld_136 *** Hyper 51 Chr 20 58855291 58855453 GNAS RhBrn_1000 *** Hyper 52 Chr 20 58889570 58890047 GNAS HuBld_1 *** Hyper 53 Chr 20 58890242 58890319 GNAS RhBld_1004 *** Hyper Chr 21 43725878 43725960 PDXK HuBld_195 *** Hypo 55 Chr 21 43727343 43727431 PDXK RhBld_1007 *** Hypo 56 Chr 21 43758088 43758098 PDXK RhBrn_1005 *** Hypo 57 Chr 21 43758106 43758177 PDXK RhBrn_1006 *** Hypo 58 Chr 21 43758178 43758183 PDXK RhBrn_1007 *** Hypo 59 Chr 4 2805929 2805990 SH3BP2 HuBld_199 ** Hypo 60 Chr 4 2825167 2825265 SH3BP2 RhBrn_141 ** Hypo 61 Chr 5 172669962 172670083 NEURL1B RhBrn_145 ** Hyper 62 Chr 5 172683900 172684098 NEURL1B HuBld_9 ** Hyper 63 Chr 7 1946572 1946581 MAD1L1 RhBrn_97 ** Hypo 64 Chr 7 1946583 1946636 MAD1L1 RhBrn_1003 ** Hypo 65 Chr 7 2113040 2113199 MAD1L1 HuBld_121 ** Hypo 66 Chr 7 50782213 50782314 GRB10 HuBld_52 *** Hyper 67 Chr 7 50782337 50782376 GRB10 RhBrn_1001 *** Hyper 68 Chr 7 50783121 50783181 GRB10 RhBld_1005 *** Hyper 69 Chr 7 94656373 94656577 PEG10 HuBld_60 ** Hypo 70 Chr 7 94658334 94658421 PEG10 RhBrn_68 ** Hypo 71 Chr 7 94658422 94658431 PEG10 RhBrn_1008 ** Hypo 72 Chr 8 140098781 140098880 TRAPPC9 RhBrn_192 *** Hyper 73 Chr 8 140098798 140098899 TRAPPC9 RhBld_208 *** Hyper 74 Chr 8 140099819 140100255 TRAPPC9 HuBld_12 *** Hyper ** monkey brain and human blood overlap ## monkey blood and human blood overlap *** monkey brain, monkey blood, and human blood overlap

TABLE 3 DMR Sequences: SEQ ID NO: Chr. Start End hg38coord cdna  1 Chr1   3503131   3503245 chr1: CGCTGAGGCCCTGAGGACACACCCTGGTGAACCCTTGTCACCAGGGCCCAT 3503131- CCCCAGGGGCACCCGCCCATAGGGACACAGGCACGTCCCTGGGACTACAG 3503245 GCCTGGCACTCACC  2 Chr1   3540349   3540490 chr1: CGGGTTTCCCGCTGCACTGGGAAGACAGCCAGCTGAAGAATGTTGGCCTGG 3540349- GGAGGCCCAGATTCAGCCACCCACAGGAACGTGGCCCCAGCTTTGCAACCG 3540490 GAAGGCCCAGGTTCAGGCCTGGGCTCCAGGGCCCATGGGC  3 Chr1  27349740  27349796 chr1: CGGTGTCCAGCCTTAACTCCTCCACGGTGAGGCGGGAGGGAGGGGACCCG 27349740- GGCGGCC 27349796  4 Chr1  27349814  27350119 chr1: CGATGCGTAGCCCCTGCCTGCCCCTCCCTCGCCGCGGGACCCACCGCTGCA 27349814- GCCCCCCAGCCTGCCACCTATGACCCGGGTCTGAAGCCTCCGCGCTGCCCG 27350119 CGGCCCCGACGTGAGCCCTGCGAGCGGCCCTGACTCCCACCCACTCCCGTC CGCAGCTGAGCGGCAGCCAGATGAGCCTGTCAGGCGACGCGGAGGCGGTG CAGGTCCGCGGCTCCGTGCACTTCGCGCTGCACTACGAGCCGGGCGCCGCC GAGCTGCGCGTGCACGTGATCCAGTGCCAGGGCCTGGCCGCCGCCCGGCGC C  5 Chr1  41540915  41541160 chr1: CGGGTTTAGCTGGACTCTAAATGGACACTGCAACCACACTGGTGCTCCAGA 41540915- CATAAACAGCCAGTAGGTGAGTGGGTGGGAAAACAGGAAGGAAGGGAGG 41541160 GTGTGGTCACGGCTCAGAGGACTGAGGTGGCCTGTCTGATTAGGACGCTGC GAGTGCAGTGGTTAGGCATGGGGTGTTGATGCATCAGACTGCCGAGTTCAA ATCCTGCCTCCTCCGACCAGCTGTGTGATCCTGAGCAAGCACCC  6 Chr1  41618187  41618276 chr1: CGCTGCGGGATGGTGCCAGAGCCCGGAGCCACCAGGCTTGCCACTCTGGCT 41618187- GCCACACAGAAGAGTCTCCTTGCGCTCAGCAGACTCTGC 41618276  7 Chr4   2805929   2805990 chr4: CGCGGGGAGACGCCTGTTCTGGAGGCCAGGCCCGCAGGCAGGAAGGAAAA 2805929- GCACGGCCGGAC 2805990  8 Chr4   2825167   2825265 chr4: CGAAAAGAAAGACCTGCCCTTGGACACCAGGTGAGCCCGGGCCCAGGGCA 2825167- TACCGGGCAGTGAGGGTCCCTGGGGCGCCTGGGCCTGACCCGGGTGTCC 2825265  9 Chr5 172669962 172670083 chr5: CGTTCACGCAGCGGCCCATCCGGCTGTACGAGCAGGTGCGGCTGCGCCTGG 172669962- TGGCCGTGCGCCCTGGCTGGAGCGGCGCGCTGCGCTTCGGCTTCACCGCGC 172670083 ACGATCCGTCGCTCATGAGC 10 Chr5 172683900 172684098 chr5: CGAGCTGCCCGCCGACCCAGACGCGCTGCTCGACCGCAAAGAGTACTGGGT 172683900- GGTGGCGCGCGCCGGGCCCGTGCCGAGCGGCGGCGACGCGCTCAGCTTCAC 172684098 GCTGCGGCCCGGCGGCGACGTGCTCCTGGGCATCAACGGGCGTCCGCGCGG CCGCCTGCTGTGCGTCGACACCACGCAGGCGCTCTGGGCCTTCTTC 11 Chr7   1946572   1946581 chr7: TGACTCAACA 1946572- 1946581 12 Chr7   1946583   1946636 chr7: AAATCTTTCACTTGCAGAGCGAGCAGGCGCTCTGGTGCTGCTACCCAGCGC 1946583- GGT 1946636 13 Chr7   2113040   2113199 chr7: CGACGAGGGGCAGAGCCTCCCTCAGCAAAGCGTCCCACTCAGGAAACGGG 2113040- GACGAGGGGCAGAGCCTCCCTCAGCAAAGCGTCCCACTCAGGAAACGGGG 2113199 ACGAGGGGCAGAGCCTCCCTCAGCAAAGCGTCCCACTCAGGAAACACGGA AGAGACGGGC 14 Chr7  50782213  50782314 chr7: CGGCAACGAAGCTCGGGATCTCGGACTGCAGCGAGCCCGCGGCAGGCGGG 50782213- CAGGGGGCCGCGCGGCAAGACCTCCCCGCCTCCCTCCCGGGCCCTGTCCGC 50782314 C 15 Chr7  50782337  50782376 chr7: GCGCAGGCCGATCCGCCCGCCGCCCCGGCTCGCGCCCACC 50782337- 50782376 16 Chr7  50783121  50783181 chr7: GCAGACAGGCGGGGGACATCGCGGCCGCGGCAAGCTAGAGATGCCGCCTG 50783121- CTCGAGCAACC 50783181 17 Chr7  94656373  94656577 chr7: CGCGCTTCAACTTCGGTTGGTGTGTGTCGAAGAAACCTGACTGCGCCCTGA 94656373- GGAGAACAGCGGAGAAGGTCCACCGAGCCTGGCGAAAGGTCCGCTGAGCG 94656577 GGCTGTCGTCCGGAGCCACTCCGGGCTGCGGAGCACCCAGTGGAGACCGCG CCTGGCTCAGGTGTGGGACCCCATCCTTCCTGTCTTCGCAGAGGAGTCCTC GC 18 Chr7  94658334  94658421 chr7: CTGGGCCCGCCTCCTCTGAGGTGAACTGCCCAGGCCCCGCCTCTCCTGGGC 94658334- CCGCCTCCTCTGATGTGAGCTCACCCAGATCCCACCT 94658421 19 Chr7  94658422  94658431 chr7: CCCCAGGCCC 94658422- 94658431 20 Chr8 140098781 140098880 chr8: CGCCCACCCAGGTCCTCCGCAGCTGTCCGCAGGGGAAGACACCAGCTAGAT 140098781- GTAAGTGCGCAGCTGCAGCAATCCCGCGATCCACAAAGTAATGACGCCC 140098880 21 Chr8 140098798 140098899 chr8: CGCAGCTGTCCGCAGGGGAAGACACCAGCTAGATGTAAGTGCGCAGCTGC 140098798- AGCAATCCCGCGATCCACAAAGTAATGACGCCCGCCCAGATCCTCCGCAGC 140098899 C 22 Chr8 140099819 140100255 chr8: CGCTGGTCCTCCGCAGCCTTCTCCAGGGGAGGACACCCAGCTAGGTCTCTG 140099819- CGCAGCTGCAGGAGTGCCACAATCCTCAGGGTACTGACGCTCACCCAGGTC 140100255 CTCCGCAGCCTTCCGCAGGGGAGATACCCAGCTAGGTCTCAGCGCGCAGCT TCAGCATCCCCGCGATCCGCAGAGTATTGACGCCCACCCGGGTCCTCCGCA GCCTAGAGCAAGGGACTGCGGAACGAGTGCCGCAATCTTCAGGGTATTGAC GCCCACCCGGGTCCTCCGCAGCCAAGAGCAAGGGACTGCGGAAGGAGTGC CGCAATCTTCAGGGTATTGACGCCCACCCGGGTCCTCCGCAGCCTAGAGCA GGGAACTGCGGAAAGAGTGCCACAATCCTCAGGGTATTGACGCCCACCCA AGTCCTCCGCAGCCTTCCGCAGGGGAGATAC 23 Chr10    309028    309164 chr10: CGGAGCGGCTGCTGACGGCGATAAGGGAAGGCACCATGTCCCACGCACTTC 309028- ACCTAAGCAACAATGAACGGGCACCTCTACAGTCACCAAGTGGAAGATGA 309164 TCTGTTTCAACGGGGGAAGTCTGCAGTAAAAATGAC 24 Chr10    329499    329561 chr10: CGTGTCTCGGACTTTGTACTGACTCACGGCAAGAAGCCACAAGGCGGGGTT 329499- GGTTTCCAGCTC 329561 25 Chr10    355287    355459 chr10: CGACACGCGCTTCTCTGGCAGAGGAGGAGGAGAGGTTGTTCCTATGAACTA 355287- AGCCACGTGCAGAGAATGGTCTGATAACTGAAACTCAAACCAGAGAGTCG 355459 GGGAATAATTTCGTGATGCTGCTGGCATTTCCTTTTGTCTTCAATCTGCTG CTTCGCACACTAAGATTTTGA 26 Chr10    355461    355490 chr10: ACTCAGCAATTCTAAACAGCCATGACTTTT 355461- 355490 27 Chr10    355492    355503 chr10: GAAGAGTTGCAA 355492- 355503 28 Chr10    355504    355516 chr10: GTACCTATACTTG 355504- 355516 29 Chr10    355517    355541 chr10: TCAAGAAGACTTACATTTTTCTTCC 355517- 355541 30 Chr10    413853    414117 chr10: CGTTCGGGAGTGGCTGTGCGAGGGGGTGGGCAAAGGGCAGAGAGTGAGCC 413853- TGGGGATTACCGTAAGTGAGGATGTAGAGGGGCTTCCCGTTGGTGTCCATG 414117 GTGGTCAGGCAGGGCGCCTTGGGCGAGATGGTGCCCCACCTCTGCAGTGCG GCCTCCAGCGACGGCGGCCAGTTCGTGACCACGCCCAGCTGCTCTCCGCGC ATGGCCAGCATCTGGGCCCCCTCCGGCTTTGGTTGGTTCGGATCCGGTTGT TGAACTAAATC 31 Chr10    484804    484931 chr10: CGGTTCCCTGCGGTGCTGGCCACCCGCTCCCGAGCCGCAGCTTCTCGGACG 484804- TCGCACACCCCGATGTGGGCAGAGCGGAATGTTCTCCTCGGCGCTCCTTCA 484931 CTGTGCTGCAGTCTACACCGAACCAC 32 Chr10 132607036 132607056 chr10: CGGCTTGTGCTGAGTGCTCGC 132607036- 132607056 Chr10 132607057 132607061 chr10:  GCTCA 132607057- 132607061 34 Chr10 132616356 132616412 chr10: CGTGGCGTGCGGGGACGCCGTGGGCGTGGTGTGAGGTATGTGGCGTGCGG 132616356- GGACGCC 132616412 35 Chr11   2133265   2133335 chr11: CGCTCTTCCGCCTGAGCCGCCCGCCTGACCTGACAGGCCACCCCTGTGACT 2133265- GATCAGTGACTTGAGCTAAT 2133335 36 Chr11   2133341   2133722 chr11: CGGGCAGAGGGACAGAAGGAGCCAGCGTCTGAGCTGCTCCCGGGCCACAC 2133341- AGCAAGCAAGGAAGTCACGGGTCCTTGTCCCTGGCCAAGAGGTCCCAGAG 2133722 GCCACAGGAAACGCTGGGCGCCCGAAGCCCTATTTCTCTGTCTCTAGAGAG TGGGAAAGGGGCCCAGGACCCTCACCGGAAGCACGGTCGGAGGGGTCGAC ACGTCCCTCTCGGACTTGGCGGGGGTAGCACAGTACGTCTCCAGGAGGGCC AGGTCACAGCTGCGGAAACAGCACTCCTCAACGATGCCACGGCTGCGACG GCTCACACGGCTTGCGGGCCTGCCTGGAAGTCCCACAGCACAGAGAGAGCC GTGTTAGCACCGCACTGACCCCAGCCCCC 37 Chr11 133081982 133082177 chr11: CGGGAAGTTCTGTCCCTGCTCCCGAGTGTGCCCAGAGTCCTGCCGTTTCCT 133081982- TCTAGCGCGCGTTCTTTACTGGCGCCATTCCTGCTGCTAAGAGCCCTGAGA 133082177 CGGCCGGGGGTGACCCGGGCCCAGAGCAGCTCCCGGCTCAGGGACCCCTCC CCAGGCCAAGGGCAGGACAAGCCCGGGCCTGGGCCTCCGCCTC 38 Chr12   1811666   1811837 chr12: CGCGTTGCCGCCCAGAATTTGCGCTGGAGGAATTCCAGCTTCATTTGGACG 1811666- CCCGCGGCTACAGGGCAGAAAGAGAGAGGGCAAGGCCAGGGAAGAGACG 1811837 GGGAGAGAAAAAAATAGAGTCAAGTTAAAGAGAGGAGGTGCTTCCGCAGG AACTGAGGAGAGAGACCGCAGC 39 Chr12   1838231   1838295 chr12: CGGTGGTGTTATACACGGCAGTGACGCGCAGCCCGCCACTGCCCCCGTGGC 1838231- TGGGCTGAGTGCCC 1838295 40 Chr12   1842428   1842506 chr12: CGCGGTTGTTTTCCTTCTTTTGGGGTGGAAGGGAGTGTGCAGAGGTGGCCA 1842428- TGTGTCTAAGCGTGTGTGTGCGCTGAGC 1842506 41 Chr12 123034226 123034317 chr12: CGTCTGGGCCAGGGAGATAATGGTGCTGAACGCAAGGGCAAGTGTTCGCGT 123034226- TGTAGGCGGCGGGACACAGTGCCGGAAAGCAATCTGATGCC 123034317 42 Chr12 123077953 123078020 chr12: CACGCAGCTCTCCCAGCAGCCCATGCCTGGAGACAGAGGACACTGAGGAG 123077953- CACGCGTGTCCCCAGGAT 123078020 43 Chr16  88500291  88500408 chr16: CGGGGACACAGCCAGCTCCCCCCATGAGCTGGTGGCCTCGTCAGGAAGACG 88500291- GCCACAGGGCGCTCTTGGGAGGACCCTTGGGACAGTGGGCAGGCGCTGGG 88500408 CAAGCCACAAGCGTGTC 44 Chr16  88534642  88534701 chr16: CGGCCGACCGCGGCCCCTCGCCCGCTCCCGCCCCCGCCGCCTCCCCGCAGC 88534642- CCGGGTCCC 88534701 Chr17    410141    410147 chr17: CGCACCG 410141- 410147 46 Chr17    414205    414425 chr17: CGTATCTGAAGGAAACAGATGTTCGGTACACGGACGACGCCGACTCTCCCA 414205- TCACCAAGCTGCCCTCGGTTGCCCAGGAGAGCCACAGTGCCTTGAGAACAT 414425 AAGCAATTTAGTGAACAGAGTTCTTTTCAGAATTTCCTTTTTCTTAAGTAA GCATCTCTGTTACTTAATTTCTCACCACAGCTAGATGTCTATAATCTGCCC CAAAAAGAAAAGAAAGC 47 Chr17   2837445   2837518 chr17: CGGAGCAGGCAGAAAGGCATATTCCGCTTCGTCTGGTGATGGGCATCGGGA 2837445- GTCTCTGGCCGAGTCAGCTCCTC 2837518 48 Chr17   2852762   2852873 chr17: CGGGAGGGGGCTGGGAGGCTGGGCAGCACCTGGAAGTGGATGAGGGCGAT 2852762- TGTGAGCGAGGCCCCGCGCCGATGGTAGGGACCAGGCCACAGCCCTTTCCC 2852873 CAGGAGCCGGC 49 Chr17  82235989  82236062 chr17: CGGAACCAACCCTCCTGGCCATGGGAGGGGCCGTGGTGGACGAGGGCCCC 82235989- ACAGGCGTCAAGGCCCCTGACGGC 82236062 50 Chr17  82238736  82238899 chr17: CGTGTTCATCCTGGCGGGGGCCGAGGTGCTCACCTCCTCCCTGATTTTGCT 82238736- GCTGGGCAACTTCTTCTGCATTAGGAAGAAGCCCAAAGAGCCACAGCCTGA 82238899 GGTGGCGGCCGCGGAGGAGGAGAAGCTCCACAAGCCTCCTGCAGACTCGGG GGTGGACTTGC 51 Chr18  79436203  79436269 chr18: CGCTTTTCAGAAACGAGGCTCATCGCACTGGCCTGGGGGCGCGAGGACGAG 79436203- GCCGTGGGTAGTGGGC 79436269 52 Chr18  79509085  79509203 chr18: CGCATGGAAGGAAACGCCATTGCTGGGCAGTGTTGCAGCCTCCGCAGAGGT 79509085- GTGTGGGCTCCGGGGAGAGGGACGTGCTGGCCCCTGTGCAGTGGCGTGGCC 79509203 CGTGTCCTTTCCCCGCC 53 Chr18  79523293  79523358 chr18: CGTTCAGGCCCTGGCAGCTCCGTTCTGGCCCTCATCATTCCCAGCATAGAG 79523293- AAACAAAACTCCTGC 79523358 Chr19    659125    659132 chr19: AGAGGCAG 659125- 659132 55 Chr19    659138    659172 chr19: GGCTGTCACTGTCACGGTATCTGGCACAACCGCAG 659138- 659172 56 Chr19    659175    659216 chr19: ACACAGAGCAAGCAGCGGCCAGAGACAGACCCAGGCCGTCTT 659175- 659216 57 Chr19    659431    659723 chr19: CGGAGGTTGCAGGCGTTCGGGGGTGGGGGGTCGGCAGGCAGAGCTGGAAC 659431- CACCCTAGGAACCACCCAGAGACGGGGAGGTCAGGGGCAAGGACGGCACG 659723 CAGGGCCACCTCCCTGCGCCCGCCTGGTTCCTGGGGGCTCAGTGCCCTCAG CAGCTCTCGCCCACACCCTACAGTCACAGCTCCAGTCAGTGCCTCCTCAGC AGGCTCGAGTCTGGGTCTGCGCAGCCGCCTGTGGCCTGAGCTCCAGCTGGC CTGTCTGGTTCCTGCCGCCACACGCCCCACTCTGGCTGAC 58 Chr19    676722    676962 chr19: CGCTGACATTTATTGAGCGCTTAGTGTCTACCTCTCCCCTCCCTGAACCTG 676722- TGCCATCCCGATAGTGCCGGAGCTCTCTTCATCTCCGTCTTCCAGATGGGG 676962 AAACTGAGGCTCAGGGTCACACAGCCTGTAGCAGGCAAAGCCAGGGTTCTA GCCGCGACCGTCCGGGTCGGTCCTGGTGCCGAGAGGTAGTGCTGGGTGTCG GGAGCCAGGCCCTCCAGCTGGGGCTGAGAGCTTTCCC 59 Chr19  18762214  18762355 chr19: CGCCCGGGAGCTGCGCACCTCCAGCAGGCACCCAGTCTAAACAAGCACAA 18762214- GGAAACACACAACATACGTGGAAGCTGGAGCCGGCGCTGGCCAGAGCGGC 18762355 CCGGTAATGCCTGACATGTGTTGGGTTGTTTGTGAACCTGCC 60 Chr19  18777827  18778074 chr19: CGGTCCCCCAGCCCATCCGCCATCCCCAGCCCGTGGTCAGGTAGAGAGTGA 18777827- GCCCCACGCCGCCCCAGGGAGGAGGCGCCAGAGCGCGGGGCAGACGCAAA 18778074 GTGAAATAAACACTATTTTGACGGCTGTCTTTTATATTTCTGAGCACACAC AGAGCCCTGGCGTCCACCGGGGCAGGCGCAAAGTGGACAGAGCATGCAGGG CGGCGGACCCCCCCACGACCCTCCTCGCCCTGTCTCCATCCCCTC 61 Chr19  56838765  56839239 chr19: CGACCAGCACACACAGCCCAAGGAGCGCGGCACTCCACAGCTTTCCATCAC 56838765- CGCAAGGCAGGCAAGCACAGCAACCGTGGCCCCGCCCCTCCCTGTGGACA 56839239 ACCCCACACCTATGCGGCAAACCGCAGCCGCCCCGATCAAAGATGGCACCC AGGTGGGCGGGGCTTGAACAGACCGTCCCGCCCATGCCACCTGCAGCCACT TCAGCCTTGCCCCGCCGCATCTGCCGCCAACCAATCCGGGCAACGCCTGCG CGGCAAACCTCAGCTGCCCCCATCAAAGATGGCGCCCAGGCGGGCGGGCCT TGTCTCGCCCAACCAACTAGGACAGCGCCTGCGCAGCAAATCTCAAGCACT TTCATTAAAGATGGCGCCCAGGTGGGTGGGGCTTGAACAAACCACTAGGTC CAATGCCACCCTGTCACTTCAGCCTTGCCCCGCCCCATCTGCCACCAACCA ACCAGGACAGCACCTGC 62 Chr19  56840640  56840712 chr19: GCCCGGCGCCCGGCGGCGCCACCAGCCCAGGGTGGACATCTCCCGCGCCTC 56840640- CCAAACCTCTCCTCCCGCAGCT 56840712 63 Chr19  56840714  56840745 chr19: CCCAGACTTCTGCACCGAGGTGCAGCTCGACG 56840714- 56840745 64 Chr20   3751818   3752296 chr20: CGACGTCTTCGAGCGCTTCGTGGCCGCCGAGCAGTCGGTGGCCCTGGGCGA 3751818- GGAGGTGCGGCGCAGCTACTGCCCGGCGCGTCCCGGCCAGCGGCGCGTACT 3752296 CATCAACCTGTACTGCTGCGCGGCAGAGGATGCGCGCTTCATCACCGACCC CGGCGTGCGCAAATGCGGCGCGCTCAGCCTCGAGCTTGAGCCCGCCGACTG CGGCCAGGACACCGCCGGCGCGCCTCCCGGCCGCCGCGAGATCCGCGCCGC CATGCAGTTTGGCGACACCGAAATTAAGGTCACCGCCGTCGACGTCAGCAC CAATCGCTCCGTGCGCGCGTCCATCGACTTTCTTTCCAACTGAGGGCGCGC CGGCGCGGTGCCAGCGCCGTCTGCCCGGCCCCGCCCTCTTTCGGTTCAGGG GCCTGCGGAGCGGGTTGGGGCGGGGGAAACGATAGTTCTGCAGTCTGCGC CTTTCCACGCCCTCCAGCCCC 65 Chr20   3751944   3752172 chr20: AGAGGATGCGCGCTTCATCACCGACCCCGGCGTGCGCAAATGCGGCGCGCT 3751944- CAGCCTCGAGCTTGAGCCCGCCGACTGCGGCCAGGACACCGCCGGCGCGCC 3752172 TCCCGGCCGCCGCGAGATCCGCGCCGCCATGCAGTTTGGCGACACCGAAAT TAAGGTCACCGCCGTCGACGTCAGCACCAATCGCTCCGTGCGCGCGTCCAT CGACTTTCTTTCCAACTGAGGGCGC 66 Chr20  58839989  58840198 chr20: CGGGCCAGCTTCTCACCTCATAGGGTGTACCTTTCCCGGCTCCAGCAGCCA 58839989- ATGTGCTTCGGAGCCACTCTCTGCAGAGCCAGAGGGCAGGCCGGCTTCTCG 58840198 GTGTGTGCCTAAGAGGATGGATCGGAGGTCCCGGGCTCAGCAGTGGCGCCG AGCTCGCCATAATTACAACGACCTGTGCCCGCCCATAGGCCGCCGGGCAGC CACCGC 67 Chr20  58850827  58850895 chr20: CGCCATACACCCGCCCCCCACCGGCTTCCAACCACCCCAGCAGCACCTCTT 58850827- CGGGCGTTCCAACGCGGC 58850895 68 Chr20  58855291  58855453 chr20: GAAAAGATGGGCTACATGTGTACGCACCGCCTGCTGCTTCTAGGTAATGCG 58855291- GCGGACTCTGCCTGCGGGCAGCAGGGCCGCCGGGGAACCGGGGAGGGGGT 58855453 GGCAGGGCTGCCTGGTGGGGCTAGGGGCTCCGCAGTGGGAGGAGGGGGTC CAGCCAAAGGCG 69 Chr20  58889570  58890047 chr20: CGCGCCTTTGCACTTTTCTTTTTGAGTTGACATTTCTTGGTGCTTTTTGGT 58889570- TTCTCGCTGTTGTTGGGTGCTTTTTGGTTTGTTCTTGTCCCTTTTTCGTTT 58890047 GCTCATCCTTTTTGGCGCTAACTCTTAGGCAGCCAGCCCAGCAGCCCGAAG CCCGGGCAGCCGCGCTCCGCGGCCCCGGGGCAGCGCGGCGGGAACCGCAGC CAAGCCCCCCGACACGGGGCGCACGGGGGCCGGGCAGCCCGAGGCCGGGGG CAAGCAGGGAGCCCGGGCCAGGCGCGAGCCGAGCTCCCCGAGGTGGCCGGG CCACCATGCTGAAGATGGCCATGAAGCTCAAAGCCCGGGCGGCGGAGAGCG AGAAGAAGACGGCCGCGGCGGCTGCCGAGGTGGCTGCCGAAGCTGCGGCGG CGGCTGCGGCGTTGGCCGAGCCGAGAGAGCCGCTCGCGCCGCGGAAGAGC GGGGACCCCGAGAAGCTCGC 70 Chr20  58890242  58890319 chr20: GATGCCCCGAGGCCGCCGCCGCCGCGGCCGCCGCCGACGACGACGAGGGC 58890242- GCCGAGGAGGGCGCCGTCGGGGGCGCCG 58890319 71 Chr21  43725878  43725960 chr21: CGGTGGCCCGCACTAACTTCCTTAGAGGTGATGCTGATGCTGTATGTTGGA 43725878- GACGCTTCTGAGTGTCCTCGGAACGTTCCCAC 43725960 72 Chr21  43727343  43727431 chr21: GCCGAGGAGGGGCCGGCAGCGCCTCCCTTCCTGCCCACAGAGCAGCCGCCT 43727343- TGTGCCCATCTATTCCCCGGCTCTGCATGGGGCCTCTG 43727431 73 Chr21  43758088  43758098 chr21: GCAGTGTCAGG 43758088- 43758098 74 Chr21  43758106  43758177 chr21: CTCCTTCTGCCCCTGCAGTGGGTGTTACGGGCGGTGTGCCCTGGCGAGCAA 43758106- GCTTTGATTCTTGGTTCTTTG 43758177 Chr21  43758178  43758183 chr21: AGCTCG 43758178- 43758183

Any combination of DMRs outlined in Table 2 may be used to diagnose or give a prognosis of AT or trait-like anxiety in a human or non-human primate. Any combination of DMRs outlined in Table 2 may be used in an assay to quantify methylation. Any combination of DMRs outlined in Table 2 or DMR-associated genes outline in Table 1 may be used in an assay to amplify the DMRs or DMR-associated genes for sequencing to quantify methylation.

In some embodiments, the DMRs of interest are SEQ ID NOs: 7-18, 50-53, 55-59, 67-69, 73, and 74, AGAGGCAG, and AGCTCG. In some embodiments, the DMR-associated genes of interest are DIP2C, GRB10, INPP5A, GNAS, PDXK, and TRAPPC9. These DMRs and DMR-associated genes showed differential methylation across samples from non-human primate brain, non-human primate blood, and human blood. In some embodiments, at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, at least 25, at least 26, at least 27, or all 28 of the DMRs of SEQ ID NOs: 7-18, 50-53, 55-59, 67-69, 73, and 74, AGAGGCAG, and AGCTCG are assayed to diagnose or give a prognosis of AT or trait-like anxiety in a human or non-human primate. In some embodiments, at least 1, at least 2, at least 3, at least 4, at least 5, at least or all 6 of the DMR-associated genes are assayed to diagnose or give a prognosis of AT or trait-like anxiety in a human or non-human primate.

In some embodiments, the DMRs of interest are SEQ ID NOs:3-6, 19-20, 27-32, and 34-37 and GCTCA. In some embodiments, the DMR-associated genes of interest are HIVEP3, C17orf97, ZFPM1, RAP1GAP2, NFATC1, IGF2, SLC16A3, and SYTL1. These DMRs and DMR-associated genes showed differential methylation across samples from non-human primate blood and human blood. In some embodiments, at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, or all 17 of these DMRs are assayed to diagnose or given a prognosis of AT or trait-like anxiety in a human or non-human primate. In some embodiments, at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7 or all 8 of the DMR-associated genes are assayed to diagnose or give a prognosis of AT or trait-like anxiety in a human or non-human primate.

In some embodiments, the DMRs of interest are SEQ ID NOs: 1-2, 21-26, 38-44, 46-49, 60-66, and 70-72 and CGCACCG. In some embodiments, the DMR-associated genes of interest are CACNA2D4, CRTC1, MEGF6, OPCML, PITPNM2, ZIM2, RNF126, FSTL3, SH3BP2, NEURL1B, MAD1L1, HSPA12B, PEG10, and PEG3. These DMRs and DMR-associated genes showed differential methylation across samples from human blood and non-human primate brain. In some embodiments, at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, at least 14, at least 15, at least 16, at least 17, at least 18, at least 19, at least 20, at least 21, at least 22, at least 23, at least 24, at least 25, at least 26, at least 27, at least 28, at least 29, or all 30 of these DMRs are assayed to diagnose or give a prognosis of AT or trait-like anxiety in a human or non-human primate. In some embodiments, at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9, at least 10, at least 11, at least 12, at least 13, or all 14 of the DMR-associated genes are assayed to diagnose or give a prognosis of AT or trait-like anxiety in a human or non-human primate.

Biomarker Panels

In some embodiments, the biomarkers described herein are used in the production of a biomarker panel for use in assaying DNA methylation. The biomarker panel includes probes or primers specific to the sequences of the DMRs or DMR-associated genes disclosed herein. In some embodiments, the biomarker panel includes probes or primers specific to the sequences of the DMR-associated genes listed in Table 1. In some embodiments, the biomarker panel includes probes or primers specific to the DMRs listed in Table 2.

Primers specific to the DMRs or DMR-associated genes disclosed herein are between about 10 base pairs (bp) and about 40 bp and are complementary to sequences upstream and downstream of the DMR or DMR-associated gene of interest. Generally, a pair of forward and reverse primers that are designed to be complementary to the sequences flanking the DMR or DMR-associated gene are included. The size of the fragment to be amplified by the primer pair can range from less than 50 bp to greater than 10,000 bp. Primers can be designed that are complementary to a sequence less than 50 bp upstream of the DMR or more than 1,000 bp upstream depending on the sequence technology selected and the application of the biomarker panel. Therefore, it is possible to design many permutations of primer sets that are capable of amplifying a given DMR or DMR-associated gene of interest. For example, a given sample containing genomic DNA with a 500 bp DMR, a primer set can be designed to amplify i) the exact target region; or ii) a region encompassing the DMR including upstream and downstream regions.

Probes specific to the DMRs or DMR-associated genes disclosed herein are between about 10 bp and about 40 bp and are commentary to sequences including or adjacent to the DMR or DMR-associated gene of interest. In some embodiments, the probe is complementary to the DMR of interest.

The disclosure includes a number of preferred primers and probes for amplification, selection, and identification of specific DMRs or DMR-associated genes. However, a skilled artisan will appreciate that the DMRs and DMR-associated genes disclosed can be amplified, selected, and identified by primers and probes other than those specific disclosed, which have been presented for purposes of illustration. It is contemplated that the biomarker panel is compatible with a number of amplification and sequencing schemes and the scope of the claims should not be limited to the description of the embodiments contained herein.

Probes or primers for use in the biomarker panels described herein may be fused to a tag or label. Suitable tags and labels are known in the art, including but not limited to fluorescent labels (e.g., GFP, RFP, etc.), biotin, and combinations thereof. In some embodiments, the probe or primer is biotinylated and the biotinylated probe or primer bound sequence can be purified or captured with a streptavidin bound substrate.

In some embodiments, the primers or probes are covalently or non-covalently linked to a substrate. Suitable substrates for the biomarker panel include a bead, a plate, a microfluidic devise, a cuvette, a chip, a multiwell plate (e.g., 6-, 12-, 24-, 48-, 96-, 384-, or 1536-well plates).

In some embodiments, the biomarker panel is a microarray.

In some embodiments, the primers or probes are biotinylated and bind to streptavidin coated substrates for selection of the DMRs or DMR-associated genes targeted by the probe or primers. In some embodiments, the streptavidin-coated substrates are beads.

Methods

In some aspects, described herein are methods to assay the methylation status of DMRs or DMR-associated genes described herein to diagnose or give a prognosis for AT or trait-like anxiety in an individual. Methylation levels of at least one DMR or DMR-associated gene recited in Table 2, or any combination of DMRs or DMR-associated genes, is measured in target DNA from a blood sample or saliva sample from a human or non-human primate.

Methylation may be quantified by any suitable means known in the art. Suitable methods for assaying quantification are disclosed, for example, by Kurdyukov and Bullock (“DNA methylation analysis: Choosing the right method,” Biology, 2016, 5(3)). Suitable methods for quantifying or assaying methylation may include, but are not limited to methylation specific polymerase chain reaction (PCR), high resolution melting, cold-PCR, pyrosequencing, PCR and sequencing, bead array, and digestion-based assay followed by PCR or quantitative PCR (qPCR).

In some embodiments, the target DNA is bisulfite modified. Bisulfite treatment mediates the deamination of cytosine to uracil, whereby the modified uracil residue will be read as a thymine as determined by PCR-amplification and sequencing. 5mC resides are protected from this conversion and will remain as cytosine.

To examine the methylation status of the DMR or DMR-associated gene, target genomic DNA may be isolated from a blood sample or a saliva sample from a subject. In some embodiments, the target DNA is isolated from a blood sample from a human or non-human primate. In some embodiments, the target DNA is isolated from a saliva sample from a human or non-human primate.

Following isolation of target DNA, the target DNA will be contacted with probes specific to the DMRs outlined in Table 2 to isolate and enrich these genomic regions from the target DNA sample. In some embodiments, sequences of the DMR is used as bait to isolate the genomic regions of interest for amplification and sequencing.

After isolation and enrichment of the genomic regions within the target DNA that include the DMR, methylated adapters are ligated to the enriched regions. The sample with the ligated methylated adapters may then be subject to sodium bisulfite modification.

In general, target DNA or bisulfite modified target DNA is subject to amplification. The amplification may be polymerase chain reaction (PCR) amplification. PCR amplification will include single or multiple pair(s) of primers and probes at specific DMRs within the DIP2C, GRB10, INPP5A, C17ORF97, PDXK, CACNA2D4, TRAPPC9, CRTC1, MEGF6, HIVEP3, OPCML, PITPNM2, ZFPM1, RAP1GAP2, NFATC1, RNF126, FSTL3, GNAS, SH3BP2, NEURL1B, MAD1L1, HSPA12B, IGF2, PEG10, PEG3, SLC16A3, SYTL1, and ZIM2 genes as outlined in Table 2. The target DNA amplification and methylation quantification will be evaluated in one or multiple tubes.

In some embodiments, methylation is quantified by amplification and sequencing of target DNA. Bisulfite modified target DNA may be subject to PCR to amplify target regions outlined in Table 2. The PCR reaction mixture typically includes at least one pair of primers designed to target a DMR detailed in Table 2, PCR buffer, dNTPs (e.g., adenine, thymine, cytosine and guanine), MgCl₂, and polymerase. PCR amplification generally includes the steps of heating the reaction mixture to separate the strands of the target DNA, annealing the primers to the target DNA by cooling the reaction mixture, allowing the polymerase to extend the primers by addition of NTPs, and repeating the process at least 2, at least 5, at least 10, at least 15, at least 20, at least 25, or at least 30 times to produce a PCR amplification product. If the target DNA in the reaction mixture is single stranded, the initial heating step may be omitted, however this heating step will need to be included when the second and subsequent times the reaction is completed to separate the extended primer strands from the opposite strand and DNA (e.g., the target DNA or another previously extended primer strand). In some embodiments, the target DNA is bisulfite modified prior to amplification.

In some embodiments, the bisulfite modified target DNA is used in a methylation-specific-quantitative PCR (MS-QPCR) reaction such as MethylLight (WO 2000/070090A1) or HeavyMethyl (WO 2002/072880A2). For example, a reaction mixture for use in a MethylLight methylation specific PCR reaction would contain primers and probes specific to the DMRs recited in Table 2, PCR buffer, dNTPs (e.g., adenine, thymine, cytosine and guanine), MgCl₂, and polymerase. A typical kit for methylation specific PCR may include primers and probes specific to the DMRs recited in Table 2, wild type reference gene primers such as β-actin, PCR buffer, dNTPs, MgCl₂, polymerase, positive and negative methylation controls, and a dilution reference. The MS-QPCR may be carried out in one or multiple reaction tubes.

In some embodiments, either the forward or reverse primer of the primer pair used in the PCR amplification reaction is biotinylated. When a biotinylated primer is used in a PCR amplification reaction, PCR products may be purified, captured, and/or sorted with a streptavidin coated substrate. In some embodiments, the substrate is a streptavidin coated bead. In some embodiments, the beads are streptavidin sepharose beads. In some embodiments, the beads are magnetic.

In some embodiments, the PCR amplification product is contacted with one or more probes specific for and complementary to a DMR detailed in Table 2. The probe may be biotinylated. The PCR amplification product and probe mixture can then be purified, captured and/or sorted with a streptavidin-coated substrate. In some embodiments, the substrate is a streptavidin-coated bead. In some embodiments, the beads are streptavidin sepharose beads. In some embodiments, the streptavidin beads are magnetic.

In some embodiments, methylation is quantified using pyrosequencing. Bisulfite modified target DNA may be subject to PCR to amplify target regions outlined in Table 2 as described above. PCR amplification products are purified, denatured to single-stranded DNA, and annealed to a sequencing primer for methylation quantification by pyrosequencing as the DMR or DMR-associated gene as detailed in Table 2. In some embodiments, methylation may be quantified with PyroMark™MD Pyrosequencing System (Qiagen) using PyroPyroMark® Gold Q96 Reagents (Qiagen, Cat #972804) (QIAGEN PyroMark Gold Q96 Reagents Handbook 08/2009, 36-38).

In some embodiments, bisulfite treated DNA is subject to an Invader® assay to detect changes in methylation. The Invader® assay entails the use of Invader® chemistry (Hologic Inc.; invaderchemistry.com; Day, S., and Mast, A. Invader assay, 2004; Chapter in Encyclopedia of Diagnostic Genomics and Proteomics. Marcel Dekker, Inc., U.S. Pat. Nos. 7,011,944; 6,913,881; 6,875,572 and 6,872,816). In the Invader® assay, one would use a structure-specific flap endonuclease (FEN) to cleave a three-dimensional complex formed by hybridization of C/T specific overlapping oligonucleotides to target DNA containing a CG site. Initial PCR amplification of the bisulfite treated target DNA may be necessary if the quantity of the bisulfite treated target DNA is less than 20 ng.

The present invention has been described in terms of one or more preferred embodiments, and it should be appreciated that many equivalents, alternatives, variations, and modifications, aside from those expressly stated, are possible and within the scope of the invention.

Example 1

To investigate the role of DNA methylation in the development and expression of AT, we previously performed genome-wide DNA methylation and mRNA expression analyses in Ce tissue collected from young monkeys repeatedly phenotyped for AT and its associated brain metabolism. This approach identified twenty-two genes with a significant correlation between AT-associated methylation levels and gene expression (P-value <0.05), including two glutamate receptors, GRIN1 and GRM5, both of which have reported roles in fear and anxiety-like behaviors. These findings are also likely to provide insights into novel treatment targets for individuals that have already developed clinically significant anxiety and depressive disorders.

The monozygotic (MZ) twin difference design is an ideal way to probe non-shared environmentally or experientially based relationships between HPA activity and amygdala function. MZ co-twins are identical for DNA sequence variants with the exception of rare somatic mutations. MZ twins reared together also share many non-genetic factors (e.g., age, parenting, etc.); thus, reliable MZ twin differences are attributed to unique or non-shared environmental factors. In this context, “environmental” simply means “non-genetic” and “unique” means “not shared with the co-twin.” Twin studies have shown that afternoon cortisol levels and amygdala volume are strongly influenced by environmental (i.e., non-genetic) factors. In addition, a substantial portion of the individual variability in anxiety level is due to variations in non-genetic factors. We recently used this design to examine the role of DNA methylation in the development and expression of human clinical anxiety using a multi-dimensional characterization method, to select monozygotic twin pairs discordant for anxiety, and whole genome DNA methylation sequencing. Profiling the whole blood DNA methylation levels in discordant individuals revealed 230 anxiety-related differentially methylated loci that were annotated to 183 genes, including several known stress-related genes such as NAV1, IGF2, GNAS, and CRTC1. As an initial validation of these findings, we tested the significance of an overlap of these data with anxiety-related differentially methylated loci in the Ce of young monkeys and found a significant overlap (P-value <0.05) of anxiety-related differentially methylated genes, including GNAS, SYN3, and JAG2. Together, these data demonstrate environmentally sensitive factors that may underlie the development of human anxiety and suggested that biomarkers of human anxiety can be detected in human blood.

Here we built upon these findings and used whole genome bisulfite sequencing to examine an average of 25.3 million CpG dinucleotides in genomic DNA from the hippocampal and blood tissue of 71 monkeys (including 23 females) and found significant overlaps of DMRs in these tissues, as well as with the previously reported anxiety-related DMRs in the monkey Ce and human blood. Together, these data suggest that blood can be used as a viable surrogate to brain tissue toward the development of a blood-based biomarker profile for clinical anxiety diagnosis, to improve estimates of clinical anxiety prognosis, and to guide personalized treatment of clinical anxiety.

Materials and Methods

Tissue acquisition and DNA/RNA extraction—The whole brains from seventy-one young monkeys (including 23 females) with an average age of 1.3±0.2 years and a broad range of AT levels (−1.48 to 1.43) were sectioned into 4.5 mm slabs and functionally guided tissue biopsies of the hippocampus were conducted following animal housing and experimental procedures that are in accordance with institutional guidelines (UW IACUC protocol #G00181). Hippocampal regions were identified, thawed briefly on wet ice, and placed on an inverted glass Petri dish on top of wet ice. A circular 3-mm punch tool was used to biopsy the region best corresponding to the hippocampus. The tissue punches were collected into 1.5-mL microfuge tubes and placed on dry ice. Once acquired, approximately thirty milligrams of tissue were homogenized with glass beads (Sigma) and DNA and RNA extraction was performed using AllPrep DNA/RNA mini kit (Qiagen).

Whole blood was collected from the same seventy-one young monkeys in a BD vacutainer CPT cell preparation tube with sodium heparin (cat #362753). The peripheral blood mononuclear cells were isolated and genomic DNA was extracted using Promega wizard genomic DNA purification kit (cat #A1120), following the manufacturers protocol.

Library Preparation and high-throughput sequencing of genomic DNA—To elucidate the utility of blood DNA methylation as a potential biomarker of anxiety and depressive disorders we will perform whole genome sequencing with bisulfite pre-treatment. This unbiased approach uses bisulfite exposure and deamination chemistry to convert unmethylated cytosines to uracil, while leaving methylated cytosines unmodified. Subsequent sequencing of the treated DNAs provides single base-pair resolution of all methylated sites in the rhesus genome, and will expose novel genes and alleles of interest if present. To achieve this goal, extracted genomic DNA was resolved on a 1% agarose gel to verify that the DNA is of high molecular weight, and quantified using Qubit (Qiagen™, Hilden, Germany). Genome-wide methylation data was generated at WuXi NextCode (Cambridge, Mass.) using whole genome HiSeq technologies from Illumina™ (e.g., HiSeq X ten). High quality genomic DNAs were forwarded to WuXi NextCode™ for sodium bisulfite treatment, library preparation, and whole genome sequencing. To process the samples, genomic DNA (500 ng) was randomly fragmented, end-repaired, and ligated to NEBNext Methylated Adapters for Illumina sequencing following the manufacturer's protocol (Illumina™). Adapter-ligated DNA fragments, ranging from 200 to 400 base pairs (bp), are purified by Sample Purification Beads (Illumina™) and then treated with sodium bisulfite (ZymoResearch™ EZ DNA methylation gold kit), that converts unmethylated cytosines to uracil and leaves methylated cytosines unaltered. Libraries of converted DNA fragments are then amplified using KAPA HiFi Hot Start Uracil+Ready Mix (KAPA Biosystems™ KM2801), and Index Primer for Illumina and Universal PCR Primer for Illumina (NEB™ E7336A). Amplicons are purified by Sample Purification Beads (Illumina™) and sequenced on a Next-Generation sequencer (Illumina™ HiSeq X ten). This approach yields ˜3 billion 150 bp-reads for each library, which provides the methylation status of ˜25 million positions in the DNA where a cytosine nucleotide is followed by a guanine nucleotide in the linear sequence of bases along its 5′→>3′ direction (i.e., CpG sites) with a coverage ≥10 reads. Image processing and sequence extraction use the standard Illumina Pipeline. Raw fastq sequence files will be forwarded to our laboratory via FedEx on an encrypted external hard drive.

DNA methylation detection—Quality control, mapping, and extraction of methylation information from the whole genome sequence data was done using bowtie2 and bismark (version 0.17.0). The average number of raw reads for each sample (N=142) was 404 million reads giving an average genomic coverage of 20.23× (median genomic coverage 19.53×). The sequence data will be filtered, and low quality and adapter sequences will be removed thereby arriving at an average genomic coverage of −20×. Cleaned sequence data are then mapped to the human Macaca mulatta (Rhesus monkey) reference genome (rheMac8), and an average of 283.3 million uniquely mapped reads were obtained for each sample, giving an average coverage of 14.16× (median coverage 13.86×). Sequence reads from both DNA strands (forward and reverse) were combined to determine the DNA methylation level at all CpG dinucleotides (˜27.4 million). Differentially methylated regions (DMRs) were identified using the DSS-single analysis method, which was selected because it incorporates the read depth into the DMR analysis and relies on smoothing so that neighborhood CpGs can be viewed as pseudo replicates and dispersion can be estimated across an entire genomic window. AT status was treated as a continuous independent variable, while methylation level was the dependent variable. All default settings were used in the DSS package (including a smoothing span of 500 bp) and the model was adjusted for gender and age. DMRs were identified using a generalized linear model in DSS, and limiting DMRs to those having a minimum of 5 consecutive CpG dinucleotides with a difference in mean methylation of 10% between the tested variables.

RNA Library Preparation and Sequencing—One hundred nanograms of total RNA from hippcampal tissue was used for sequence library construction following instructions of the NuGen mRNA sample prep kit (cat #0348). In brief, total RNA was copied into first strand cDNA using reverse transcriptase and random primers. This process was followed by second strand cDNA synthesis using DNA Polymerase I and RNaseH. The cDNA fragments were end repaired, a single “A” base was added, and then ligated to adapters. The products were gel purified and enriched by PCR to generate cDNA libraries. One hundred-cycle single-end sequencing was performed by Novogene Corporation (Sacramento, Calif. USA).

RNA-Seq Processing and Analysis—After adapter trimming of reads, a median of 20.2 million paired-end reads were obtained per sample. Quality was assessed for each pair-mate using FastQC. After reads were assured for quality, paired-end reads were aligned to the Rhesus Macaca mulatta reference genome (Mmul_8.0.1) using RSEMv1.3.1, which utilized STAR v2.7.0. RNA transcription was quantified using RSEM which resulted in quantification for ˜30,000 ensembl genes. Genes were filtered out if the total count for the gene was less than 500, or if it was present in less than 25 of the 31 samples. This resulted in a total of 12,768 ensembl genes, corresponding to a total of 11,471 gene symbols. The samples were classified as ‘high’ or ‘low’ anxiety depending on their AT_ToD score. If the score was below 0, the sample was classified as low, and if it was above 0, it was classified as high. Differential expression analysis was then performed using the DESeq function in the DESeq2 package. Any gene with a raw P-value <0.1 and a log 2 fold change >0.1 was deemed significant.

Results

The hippocampal methylome of young rhesus monkeys—To characterize the DNA methylation levels across the entire hippocampus genome (i.e., the hippocampal methylome) from young primates and reveal the epigenetic basis of anxious temperament, we extracted genomic DNA from the hippocampus of seventy-one rhesus macaques. All seventy-one monkeys were young (mean age=1.3±0.2 years) with a broad range of AT levels (−1.48 to 1.43). AT is computed as a composite measure among vocalizations, cortisol levels and time freezing (mean AT score) assessed during the no eye contact (NEC) condition of the human intruder paradigm. In this study, AT levels were assessed twice and the mean score for each monkey was used for analysis. The hippocampal genomic DNA from each monkey was treated with sodium bisulfite and sequenced on a Next-generation sequencer (Materials and Methods). This approach generated DNA methylation information at ˜27.4 million CpG dinucleotides from the hippocampus of rhesus macaques. To investigate comparisons across the seventy-one individual monkey genomes, the high quality methylation data was filtered for CpG data that had a sequence read depth greater than 2 and less than 100 occurring in a minimum of thirty-six monkeys (N=26,497,371). This final dataset revealed a bimodal distribution of DNA methylation in monkey hippocampal tissue, with the majority (>60%) of CpGs being more than 60% methylated.

To examine whether the rhesus hippocampus harbors differential DNA methylation that is related to individual differences in AT levels, the methylation data were subjected to a differential methylation analysis that employed a statistical algorithm that incorporates sequence data read depth and does not need data from biological replicates (Materials and Methods). This analytical approach, which limited positive results to differentially methylated regions (DMRs) that have a minimum of 5 adjacent CpG dinucleotides with a minimum mean methylation difference of 10% across the seventy-one monkeys, revealed a total of 645 AT-related differentially methylated regions. AT-related increases in methylation were classified as hyper-DMRs and anxiety-related decreases in methylation were classified as hypo-DMRs. A total of 222 hyper- and 423 hypo-DMRs were identified and these loci were distributed across all the autosomes (Dataset 1), suggesting a genome-wide decrease in DNA methylation is associated with AT which is consistent with previous studies. Annotation of these DMRs to genomic structures revealed 515 genes that are enriched for neuronal ontological functions, such as synapse assembly and neuron development. Comparison of these genes to the genes previously found in the Ce revealed a significant overlap (P-value <0.05), indicating common AT-related epigenetic disruptions in these two brain structures. Importantly, a significant overlap (P-value <0.05) also was found between these differentially methylated genes from the monkey brain and anxiety-related differentially methylated genes reported in human blood, suggesting that blood may be an accessible tissue of value in the identification of differential methylation associated with the risk to develop trait-like anxiety.

The whole blood methylome of young rhesus monkeys—The genomic DNA from whole blood of the same monkeys examined above was treated with sodium bisulfite and sequenced on a Next-generation sequencer (Materials and Methods). This approach generated DNA methylation information at ˜27.6 million CpG dinucleotides from the blood tissue of rhesus macaques. To investigate comparisons across the seventy-one individual monkey genomes, the high quality methylation data was filtered for CpG data that had a read depth greater than 2 and less than 100 occurring in a minimum of thirty-six monkeys (N=26,973,327). This final dataset revealed a bimodal distribution of DNA methylation in monkey hippocampal tissue, with the majority (>60%) of CpGs being more than 60% methylated.

To examine whether the rhesus blood harbors differential DNA methylation that is related to individual differences in AT levels, the methylation data were subjected to the differential methylation analysis described for the hippocampal analysis (Materials and Methods). This analytical approach revealed a total of 719 AT-related differentially methylated regions (permutation P-value <0.01). AT-related increases in methylation were classified as hyper-DMRs and anxiety-related decreases in methylation were classified as hypo-DMRs. A total of 301 hyper- and 418 hypo-DMRs were identified and these loci were distributed across all the autosomes (Dataset 1), suggesting a genome-wide increase in DNA methylation is associated with AT which is consistent with previous studies. Comparison to monkey brain DMRs finds a significant overlap (N=51; P-value <0.0001), and the test statistics of these DMRs are significantly correlated, meaning these common DMRs are largely differentially methylated in the same direction (i.e., hyper-methylated or hypo-methylated; R-squared=0.701; P-value <0.0001).

For comparisons to the anxiety-related DMRs and DMR-associated genes previously found in human blood, the DMRs found in monkeys were mapped to the human reference genome (hg38). This approach revealed an overlap of six DMR-associated genes between monkey brain, monkey blood, and human blood anxiety-related blood DMRs, including DIP2C, GRB10, and CRTC1 (FIG. 1 ). Furthermore, twelve DMR-associated genes were uniquely common to the monkey brain and human blood, and eight DMR-associated genes were uniquely common to monkey blood and human blood. These DMRs comprise multiple CpGs and a greater than 10% differential methylation related to anxiety (FIG. 2 ), which serves to substantiate these findings. Together, these data indicate that human blood contains anxiety-related changes in DNA methylation that provides the foundation for developing a blood-based biomarker profile for diagnosing the individual expression of clinical anxiety.

Using the overlapping genomic locations of the anxiety-related DMRs identified here and previously, we built a custom resequencing panel that will be used to detect deviations from healthy anxious trajectories and bolster diagnostic efforts with an epigenetic metric that integrates heritable and acquired variables that influence the expression of an anxious temperament and the development of clinical anxiety and depressive disorders. This resequencing panel will use Illumina Custom Enrichment Panel technology that enables custom panel design between 2,000-67,000 probes using DesignStudio. Nextera Flex methodologies will be used for enrichment. The initial enrichment panel (i.e., AT enrichment panel v3) will examine the DNA methylation levels at all the CpGs found in the 26 anxiety-related DMRs that are overlapping between monkey brain, monkey blood, and/or human blood (FIG. 1 ; Table 2). This resequencing panel will be employed as a blood DNA methylation biomarker diagnostic test for clinical anxiety and depressive disorders, improving estimates of prognosis and to guide personalized treatment of clinical anxiety and depressive disorders.

RNA sequencing—The RNA sequencing was conducted using the same monkey brain tissue that was used to generate the DNA methylation data. Thus, these expression data provide a direct comparison with the monkey brain DNA methylation data to begin to identify a possible mechanism (DNA methylation) for the observed changes in expression that likely drive the AT phenotype. Approximately 60 genes have correlated changes in DNA methylation and gene expression levels in the monkey brain that are linked to the AT phenotype. Notably, 50% ( 3/6) of the genes that we find differentially methylated in all three tissues (human blood, monkey brain, and monkey blood) are among these 60 genes. These gene are GRB10, PDXK, and TRAPPC9. This additional connection to gene expression changes in the brain associated with the AT phenotype makes these three gene our top candidates. Ten more genes (13 in total) that have correlated changes in DNA methylation and gene expression levels in the monkey brain, also are differentially methylated in the monkey blood. These 10 genes (BRD3, DDX50, DUSP8, EHMT1, HCN2, IL17D, MICAL3, NACC2, PKD1, and VWA1) also are top candidates.

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1-26. (canceled)
 27. A method of amplifying one or more differentially methylated region (DMR) associated genes comprising the steps of: (a) providing a reaction mixture comprising bisulfite modified target DNA from a subject and at least one pair of primers designed to amplify at least one DMR-associated gene selected from the group consisting of DIP2C, GRB10, INPP5A, GNAS, PDXK, TRAPPC9, C17ORF97, CACNA2D4, CRTC1, MEGF6, HIVEP3, OPCML, PITPNM2, ZFPM1, RAP1GAP2, NFATC1, RNF126, FSTL3, SH3BP2, NEURL1B, MAD1L1, HSPA12B, IGF2, PEG10, PEG3, SLC16A3, SYTL1, ZIM2, BRD3, DDX50, DUSP8, EHMT1, HCN2, IL17D, MICAL3, NACC2, PKD1, and VWA1, wherein the primer pair comprises a first and a second primer that are complementary to the DMR-associated gene; (b) heating the reaction mixture to a first predetermined temperature for a first predetermined time; (c) cooling the reaction mixture to a second predetermined temperature for a second predetermined time under conditions to allow the first and second primers to hybridize with their complementary sequences on the target DNA; and (d) repeating steps (b) and (c) wherein an amplified target DNA sample is formed.
 28. The method of claim 27, wherein the reaction mixture additionally comprises a polymerase and a plurality of free nucleotides comprising adenine, thymine, cytosine, and guanine.
 29. The method of claim 27, wherein the reaction mixture additionally comprises a reaction buffer and MgCl₂.
 30. The method of claim 27, wherein the primers are specific for a DMR selected from the group consisting of SEQ ID NOs:1-75.
 31. The method of claim 27, wherein at least one of the primers in the primer pair is biotinylated.
 32. The method of claim 27, wherein the target DNA is isolated from a blood sample or a saliva sample from the subject.
 33. The method of claim 27, wherein the subject is a human or non-human primate.
 34. The method of claim 27, wherein step (a) comprises providing at least two reaction mixtures, each of the at least two reaction mixtures comprising the bisulfite modified target DNA from the subject and at least one pair of primers designed to amplify at least one different DMR-associated gene.
 35. The method of claim 27, wherein step (a) comprises providing at least three reaction mixtures, each of the at least three reaction mixtures comprising the bisulfite modified target DNA from the subject and at least one pair of primers designed to amplify at least one different DMR-associated gene.
 36. The method of claim 27, wherein step (a) comprises providing at least four reaction mixtures, each of the at least four reaction mixtures comprising the bisulfite modified target DNA from the subject and at least one pair of primers designed to amplify at least one different DMR-associated gene.
 37. The method of claim 27, wherein step (a) comprises providing at least five reaction mixtures, each of the at least five reaction mixtures comprising the bisulfite modified target DNA from the subject and at least one pair of primers designed to amplify at least one different DMR-associated gene.
 38. The method of claim 27, wherein step (a) comprises providing at least 10 reaction mixtures, each of the at least 10 reaction mixtures comprising the bisulfite modified target DNA from the subject and at least one pair of primers designed to amplify at least one different DMR-associated gene.
 39. The method of claim 27, wherein step (a) comprises providing at least 15 reaction mixtures, each of the at least 15 reaction mixtures comprising the bisulfite modified target DNA from the subject and at least one pair of primers designed to amplify at least one different DMR-associated gene.
 40. The method of claim 27, wherein step (a) comprises providing at least 20 reaction mixtures, each of the at least 20 reaction mixtures comprising the bisulfite modified target DNA from the subject and at least one pair of primers designed to amplify at least one different DMR-associated gene.
 41. A method for estimating risk of anxious temperament in a subject comprising the steps of: (a) isolating and bisulfite modifying target DNA from a blood or saliva sample from the subject; (b) quantifying methylation in at least one of DMR-associated genes DIP2C, GRB10, INPP5A, GNAS, PDXK, TRAPPC9, C17ORF97, CACNA2D4, CRTC1, MEGF6, HIVEP3, OPCML, PITPNM2, ZFPM1, RAP1GAP2, NFATC1, RNF126, FSTL3, SH3BP2, NEURL1B, MAD1L1, HSPA12B, IGF2, PEG10, PEG3, SLC16A3, SYTL1, ZIM2, BRD3, DDX50, DUSP8, EHMT1, HCN2, IL17D, MICAL3, NACC2, PKD1, and VWA1 in target DNA from the subject by contacting the bisulfite modified target DNA with a primer pair directed to at least one of DMR-associated genes under conditions suitable for amplification of the DMR-associated gene to obtain methylation quantification therein; and (c) transforming the methylation quantification of the DMR-associated gene into an estimation of risk of anxious temperament, wherein a change in methylation of at least 10% compared to methylation in the same DMR-gene from a subject unaffected by anxious temperament indicates a risk of anxious temperament in the subject.
 42. A biomarker panel comprising probes specific to at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, or at least 35 of DIP2C, GRB10, INPP5A, GNAS, PDXK, TRAPPC9, C17ORF97, CACNA2D4, CRTC1, MEGF6, HIVEP3, OPCML, PITPNM2, ZFPM1, RAP1GAP2, NFATC1, RNF126, FSTL3, SH3BP2, NEURL1B, MAD1L1, HSPA12B, IGF2, PEG10, PEG3, SLC16A3, SYTL1, ZIM2, BRD3, DDX50, DUSP8, EHMT1, HCN2, IL17D, MICAL3, NACC2, PKD1, and VWA1. 